Head Trauma

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress in reducing morbidity and mortality for TBI patients in need of sedation and intensive care. This has led to increased focus on the mechanisms of secondary brain injury, typically monitored via high-frequency, multi-modal physiologic data reflecting pressure flow and oxygen delivery. However, the co...

Characterization of the Sequence of Cytopenia after Total-body Irradiation using Unsupervised Machine Learning.

Hematopoietic acute radiation syndrome (H-ARS) elicits multidimensional effects, as total-body irradiation (TBI) induced myelosuppression results in distinct patterns of loss and recovery across blood cell lineages. This study aimed to characterize the sequence of pancytopenia after TBI in male and female non-human primates (NHPs) with and without sargramostim treatment using unsupervised machine ...

Representation Learning for Cerebrovascular Autoregulation: A Model Study With Experimental Data Classification.

OBJECTIVE: Cerebrovascular autoregulation (CA) maintains adequate cerebral blood flow (CBF) during changes in cerebral perfusion pressure (CPP) and ca...

Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters.

OBJECTIVE: This study explored factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients (MHD) based on ...

Predicting seizure-free outcomes in people with treatment-resistant epilepsy: A machine learning approach.

BACKGROUND: Epilepsy surgery is an important intervention for treatment-resistant epilepsy, butthe ability to predict long-term seizure freedom post-s...

Effectiveness of transcranial direct current stimulation (tDCS) on attention and memory biases in individuals with post-traumatic stress disorder (PTSD): a randomized, single-blind, parallel-group study.

Based on neurocognitive models, the development and maintenance of post-traumatic stress disorder (PTSD) are correlated with cognitive biases, includi...

Predicting Hypertension Persistence in Coarctation of the Aorta: A Feasibility Study.

Hypertension (HTN), despite contemporary endovascular repair, is a common and challenging complication of coarctation of the aorta (CoA), and its mech...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Improved outcomes and donor utilization in heart transplantation with 10 °C static cold storage.

OBJECTIVE: To compare 10 °C static cold storage (SCS) with traditional ice for cardiac allograft preservation, its impact on post-transplant outcomes,...

Dynamic Ex-Post Baselines for Enhancing the Credibility of Improved Forest Management Carbon Offsets.

Forest carbon offsets are pivotal to the global climate strategy, yet their claimed benefits are often undermined by flawed baselines, compromising th...

Could sleep engineering be used to combat PTSD and depression?

Sleep engineering could be developed to provide a drug-free, non-invasive avenue to treat depression and post-traumatic stress disorder. Such an inter...

Development and proof-of-concept of a treatment target recommendation algorithm in the context of cognitive processing therapy.

Background: Cognitive Processing Therapy (CPT) is an effective, widely supported treatment for PTSD, but patient response varies considerably. Optimal...

Artificial Intelligence Impact on Radiologist Performance in Breast Cancer Screening with Digital Breast Tomosynthesis.

PURPOSE: Assess impact of artificial intelligence (AI) on radiologists' detection of cancer on digital breast tomosynthesis (DBT) exams based on densi...

3D Cardiac Magnetic Resonance Substrate Features-Based Machine Learning Model for Post-myocardial Infarction Risk Stratification: a Multicenter Study.

BACKGROUND: Accurate risk stratification post-myocardial infarction (MI) remains challenging. This study aimed to develop interpretable machine learni...

The AI Act and the MDR post-market requirements for semiautonomous AI SaMD: a radiology case study in prostate cancer.

PURPOSE: To clarify overlapping post-market obligations under the EU Artificial Intelligence Act (AIA) and EU Medical Device Regulation (MDR) for high...

Multi-branch convolutional neural network and intracranial EEG high-frequency oscillations predict post-surgical seizure outcomes.

OBJECTIVE: Pathological High-Frequency Oscillations (HFOs) identify epileptogenic cortex, but their surgical utility is unproven. Current epilepsy sur...

Active surveillance methods to identify adverse events of special interest (AESIs) following vaccination against pandemic diseases: A scoping review.

INTRODUCTION: Active post-vaccination surveillance is vital for ensuring vaccine safety, particularly in monitoring Adverse Events of Special Interest...

Optimization and External Validation of a Deep Learning Model for Segmentation and Quantification of Traumatic Brain Injury Lesions on Head Computed Tomography.

Current methods for radiological classification in traumatic brain injury (TBI), such as the Marshall and Rotterdam score, provide an incomplete descr...

Longitudinal brain-age predictions comprising long-duration spaceflight missions.

Our study investigates the effects of long-duration spaceflight on brain aging in spacefarers using structural MRI and machine learning models. Pre-, ...

Characterising processing conditions that artifactually bias human brain tissue transcriptomes.

Autopsy-derived brain tissue analysis is crucial for understanding neurobiology, but post-mortem handling can introduce artifacts. We studied adult hu...